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Title: Received signal strength based indoor positioning using a random vector functional link network
Authors: Cui, Wei
Zhang, Le
Li, Bing
Guo, Jing
Meng, Wei
Wang, Haixia
Xie, Lihua
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2017
Source: Cui, W., Zhang, L., Li, B., Guo, J., Meng, W., Wang, H., & Xie, L. (2018). Received signal strength based indoor positioning using a random vector functional link network. IEEE Transactions on Industrial Informatics, 14(5), 1846-1855. doi:10.1109/TII.2017.2760915
Journal: IEEE Transactions on Industrial Informatics
Abstract: Fingerprinting based indoor positioning system is gaining more research interest under the umbrella of location-based services. However, existing works have certain limitations in addressing issues such as noisy measurements, high computational complexity, and poor generalization ability. In this work, a random vector functional link network based approach is introduced to address these issues. In the proposed system, a subset of informative features from many randomized noisy features is selected to both reduce the computational complexity and boost the generalization ability. Moreover, the feature selector and predictor are jointly learned iteratively in a single framework based on an augmented Lagrangian method. The proposed system is appealing as it can be naturally fit into parallel or distributed computing environment. Extensive real-world indoor localization experiments are conducted on users with smartphone devices and results demonstrate the superiority of the proposed method over the existing approaches.
ISSN: 1551-3203
DOI: 10.1109/TII.2017.2760915
Rights: © 2017 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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